Abusive Head Trauma: Developing a Computational Adult Head Model to Predict Brain Deformations under Mild Accelerations
Abusive head trauma, previously termed “shaken baby syndrome”, refers to head injuries inflicted on young infants by their caregivers. There is currently a lack of scientific evidence around the causes of these injuries, but violent shaking has been implicated . Computational modelling of the infant head can help to address ambiguities surrounding the diagnosis of abusive head trauma. To validate this numerical approach, in-vivo brain deformations of the adult brain undergoing mild angular accelerations were used.
A set of mild acceleration in-vivo adult head rotation experiments were conducted. The deformations of the brain under these rotational motions were measured using tagged magnetic resonance imaging techniques. These experiments were conducted within the Center for Neuroscience and Regenerative Medicine, Bethesda, MD . A corresponding computational finite element model of the adult head undergoing mild accelerations was created using ANSYS Workbench (ANSYS, Inc.). A fluid–structure interaction model was implemented, which modelled the cerebrospinal fluid and the solid segments of the adult head. Displacements predicted by the finite element model were compared to the associated experimental data in order to verify the assumptions and parameter settings of the finite element model. Results demonstrated that the fluid–structure modelling framework could predict, to within experimental error, the deformation of the adult brain.
The overall goals of the whole project were to create a biophysically based computational model of an infant’s head, and to use this model to investigate the mechanical effects on the infant brain under a shaking motion. Such models may ultimately be used to determine the link between shaking motions and the injuries observed in infants with abusive head trauma.
KeywordsAbusive head trauma Tagged MRI In-vivo adult brain deformations Fluid structural modelling
The work presented in this paper could not have been completed without the assistance of the Image Processing Core lab at the Center for Neuroscience and Regenerative Medicine in Bethesda, MD. A special thank you must be given to Deva Chan, for her expert assistance with interpretation of the experimental data used in this project.
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